Tomographic reconstructions under unknown angles and shifts

Designed and implemented a way of recovering angles from a set of tomographic projections when the view-angles are completely unknown by exploiting the Helgason-Ludwig Consistency Conditions which relate the object moments to the projection moments. Improved the estimates by formulating the error function as a compressed sensing optimization problem taking advantage of the sparsity of signal in the DCT domain. Using techniques such as K-means clustering and PCA denoising I was able to achieve accurate reconstructions of the object.

These are the slides of my presentation given at the end, briefly summarizing all the work accomplished.


© 2018. All rights reserved.

Powered by Hydejack v7.5.0